Fast Geodesic Active Fields for Image Registration Based on Splitting and Augmented Lagrangian Approaches.

In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.

Potential approaches for more successful dendritic cell-based immunotherapy.

INTRODUCTION: Dendritic cells (DCs) are the most important antigen-presenting cell population for activating antitumor T-cell responses; therefore, they offer a unique opportunity for specific targeting of tumors. AREAS COVERED: We will discuss the critical factors for the enhancement of DC vaccine efficacy: different DC subsets, types of in vitro DC manufacturing protocol, types of tumor antigen to be loaded and finally different adjuvants for activating them. We will cover potential combinatorial strategies with immunomodulatory therapies: depleting T-regulatory (Treg) cells, blocking VEGF and blocking inhibitory signals. Furthermore, recommendations to incorporate these criteria into DC-based tumor immunotherapy will be suggested. EXPERT OPINION: Monocyte-derived DCs are the most widely used DC subset in the clinic, whereas Langerhans cells and plasmacytoid DCs are two emerging DC subsets that are highly effective in eliciting cytotoxic T lymphocyte responses. Depending on the type of tumor antigens selected for loading DCs, it is important to optimize a protocol that will generate highly potent DCs. The future aim of DC-based immunotherapy is to combine it with one or more immunomodulatory therapies, for example, Treg cell depletion, VEGF blockage and T-cell checkpoint blockage, to elicit the most optimal antitumor immunity to induce long-term remission or even cure cancer patients.

Personalized approaches to active immunotherapy in cancer

Immunotherapy is emerging as a promising anti-cancer curative modality. However, in contrast to recent advances obtained employing checkpoint blockade agents and T cell therapies, clinical efficacy of therapeutic cancer vaccines is still limited. Most vaccination attempts in the clinic represent "off-the shelf" approaches since they target common "self" tumor antigens, shared among different patients. In contrast, personalized approaches of vaccination are tailor-made for each patient and in spite being laborious, hold great potential. Recent technical advancement enabled the first steps in the clinic of personalized vaccines that target patient-specific mutated neo-antigens. Such vaccines could induce enhanced tumor-specific immune response since neo-antigens are mutation-derived antigens that can be recognized by high affinity T cells, not limited by central tolerance. Alternatively, the use of personalized vaccines based on whole autologous tumor cells, overcome the need for the identification of specific tumor antigens. Whole autologous tumor cells could be administered alone, pulsed on dendritic cells as lysate, DNA, RNA or delivered to dendritic cells in-vivo through encapsulation in nanoparticle vehicles. Such vaccines may provide a source for the full repertoire of the patient-specific tumor antigens, including its private neo-antigens. Furthermore, combining next-generation personalized vaccination with other immunotherapy modalities might be the key for achieving significant therapeutic outcome.